AIMC Topic: Reinforcement Machine Learning

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Spatio-Temporal SIR Model of Pandemic Spread During Warfare with Optimal Dual-use Health Care System Administration using Deep Reinforcement Learning.

Disaster medicine and public health preparedness Jul 21, 2025
OBJECTIVES: Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challenges to societies. Understanding the dynamics of epidemic spread during warfare is essential...
Humans Pandemics Warfare Deep Learning Models, Theoretical Reinforcement Machine Learning Computer Simulation Spatio-Temporal Analysis
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Sign potential-driven multiplicative optimization for robust deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Apr 25, 2025
Deep Reinforcement Learning (DRL) has attracted the interest of researchers due to its ability to provide valuable solutions to a variety of problems in different fields, such as robotics, autonomous driving, financial trading, and more. However, DRL...
Reinforcement, Psychology Reinforcement Machine Learning Humans Algorithms Deep Learning Neural Networks, Computer
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Enhancing the resilience of urban drainage system using deep reinforcement learning.

Water research Apr 19, 2025
Real-time control (RTC) is an effective method used in urban drainage systems (UDS) for reducing flooding and combined sewer overflows. Recently, RTC based on Deep Reinforcement Learning (DRL) has been proven to have various advantages compared to tr...
Deep Learning China Cities Reinforcement Machine Learning Rain Drainage, Sanitary Models, Theoretical Floods
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Deep reinforcement learning for decision making of autonomous vehicle in non-lane-based traffic environments.

PloS one Apr 16, 2025
Existing research on decision-making of autonomous vehicles (AVs) has mainly focused on normal road sections, with limited exploration of decision-making in complex traffic environments without lane markings. Taking toll plaza diverging area as an ex...
Decision Making Automobiles Automobile Driving Computer Simulation Deep Learning Reinforcement Machine Learning Humans Algorithms
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Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning.

Nature communications Apr 15, 2025
Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses challenges to the effective diagnosis and treatment of ccRCC. To a...
Markov Chains Kidney Neoplasms Carcinoma, Renal Cell Reinforcement Machine Learning ErbB Receptors Deep Learning Genetic Predisposition to Disease Computational Biology Humans Risk Factors
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CNRein: an evolution-aware deep reinforcement learning algorithm for single-cell DNA copy number calling.

Genome biology Apr 7, 2025
Low-pass single-cell DNA sequencing technologies and algorithmic advancements have enabled haplotype-specific copy number calling on thousands of cells within tumors. However, measurement uncertainty may result in spurious CNAs inconsistent with real...
Single-Cell Analysis Sequence Analysis, DNA Ovarian Neoplasms Reinforcement Machine Learning DNA Copy Number Variations Female Breast Neoplasms Deep Learning Humans Algorithms
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Shared autonomy between human electroencephalography and TD3 deep reinforcement learning: A multi-agent copilot approach.

Annals of the New York Academy of Sciences Mar 30, 2025
Deep reinforcement learning (RL) algorithms enable the development of fully autonomous agents that can interact with the environment. Brain-computer interface (BCI) systems decipher human implicit brain signals regardless of the explicit environment....
Brain-Computer Interfaces Reinforcement, Psychology Reinforcement Machine Learning Brain Deep Learning Electroencephalography Humans Algorithms
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Deep reinforcement learning can promote sustainable human behaviour in a common-pool resource problem.

Nature communications Mar 22, 2025
A canonical social dilemma arises when resources are allocated to people, who can either reciprocate with interest or keep the proceeds. The right resource allocation mechanisms can encourage levels of reciprocation that sustain the commons. Here, in...
Reinforcement Machine Learning Game Theory Resource Allocation Cooperative Behavior Reinforcement, Psychology Neural Networks, Computer Trust Deep Learning Humans
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Optimizing fractionation schedules for de-escalation radiotherapy in head and neck cancers using deep reinforcement learning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Mar 14, 2025
PURPOSE: Patients with locally-advanced head and neck squamous cell carcinomas (HNSCCs), particularly those related to human papillomavirus (HPV), often achieve good locoregional control (LRC), yet they suffer significant toxicities from standard che...
Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Support Vector Machine Humans Deep Learning Reinforcement Machine Learning Radiotherapy Planning, Computer-Assisted Dose Fractionation, Radiation
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Pixel level deep reinforcement learning for accurate and robust medical image segmentation.

Scientific reports Mar 10, 2025
Existing deep learning methods have achieved significant success in medical image segmentation. However, this success largely relies on stacking advanced modules and architectures, which has created a path dependency. This path dependency is unsustai...
Humans Algorithms Image Processing, Computer-Assisted Reinforcement Machine Learning Deep Learning
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